Customer Service Strategy with Artificial Intelligence can influence the way your customers interact with your brand during their buying journeys. But, can you succeed with AI if your strategy doesn’t include the human side of the business operations? Let’s discuss this wonderful human-AI relationship in customer service strategy in 2023.
My first interaction with Artificial intelligence (AI) was rather animated. It began with the Japanese maga TV series called Giant Robo, which developed my keen interest in robotics. Then came The Terminator, and a string of Hollywood movies based on the sci-fi literary works of Isaac Asimov and Robert Silverberg. I vividly remember Andrew Martin, the NDR series android assistant for housekeeping tasks, from the movie “Bicentennial Man”.
For a boy of 14, watching Robin Williams play”Bicentennial Man” was a revelation.
And, later, Will Smith’s I, Robot, became the highlight of my interactions with AI-centric research works. I had a fair idea of AI capabilities that could shape the future of our upcoming generations. In the last ten years or so, AI’s Bolt-like pace has not only accelerated the software development practices but also influenced the way these are sold and serviced in the industry. Today, AI and a range of niche machine-learning capabilities have become a staple in a majority of business activities that involve some level of human-machine interaction.
With cloud-based contact centers becoming the go-to investment hubs for omnichannel customer communication and support management, including AI-powered capabilities ensures that the agents can quickly respond to every customer query without sacrificing the quality of service at any stage. In fact, AI-assisted customer service strategy is the most effective and agile way to deliver a personalized, predictive experience that drives deeper conversations and improves customer loyalty.
Why do speed and quality of service matter to a contact center?
According to Salesforce’s “State of the Connected Customer Report”, nearly two-thirds (72%) of customers stay loyal to an organization that provides faster service. The same report also found a correlation between the use of AI technologies, such as Generative AI, and customer sentiments that influence behavior during sales, service, and support.
AI, that way not only impacts the way a brand communicates with the customers but also how agents use the same set of machine learning tools to improve their automated processes for better productivity. Overall, AI-powered customer service is a mission-critical component of any modern-day customer-centric brand.
Clearly, AI has expanded its role and capabilities in customer service operations beyond automation and predictive intelligence. However, by merely adopting AI for automation without truly empowering the agents, organizations can’t succeed, especially when AI capabilities are brought into the systems for managing customer service without enough training data to escalate the complex queries from live bots to human agents. One bad experience with the AI, just like how it works with the agents, customers could permanently abandon their interactions, and look out for alternative solutions elsewhere.
That’s why CX leaders should set a realistic roadmap for their AI-powered customer service decisions to ensure they are not making blunders that could shake their business goals in 2023. Here are five things you should do to get started with a Customer Service Strategy with Artificial Intelligence that delivers an exceptional customer experience across all touch-points.
Define “What AI in Customer Service” Means to You and Your Organization
What is the ultimate goal of your customer service team?
Are you looking to reduce the customer wait times on calls?
Do you want to improve the customer satisfaction (CSAT) scores and increase NPS?
Do you want to offer an advanced technology-powered interaction platform to your customers when they call you or chat with you through the web, mobile app, social media messengers, or emails?
Do you want to improve the quality of service and reduce the churn rate within your customer service department?
There are hundreds of questions that you could potentially think of when you are defining your AI in customer service strategy.
What you truly need to focus on is– “How well do I understand my customers? Would an AI-assisted contact center tool reduce their frustration or would it escalate the problems?”
The best way to progress with AI in a contact center is to define the frameworks.
That’s why, we have defined the role of AI in customer service as:
“A scientific approach to transforming traditional customer support activities using advanced new-age digital capabilities such as AI and automation with the sole objective of providing exceptional customer care based on instant, accurate, and personalized contact center interactions.”
Businesses fail to generate results with AI when they don’t understand what customers truly expect from them.
Customers don’t necessarily just want to chat or talk to your agents when they contact your service department. What they are truly looking for is fast, actionable, and trustworthy responses based on their needs and wants. That’s why, it is important to define the role of Artificial Intelligence in your overall customer service workflows.
There are different ways to implement AI in customer service.
The most common example is an AI-powered chatbot. More than 90% of online customer queries are fielded by AI chatbots or chat robots. Bigger brands deploy customizable chatbot interfaces to engage customers and even up-sell or cross-sell services and products. With new technologies such as generative AI and voice search, chatbot training models have seen a remarkable improvement in their self-learning capabilities, resulting in better decision-making for an improved quality of service, with little or no human interference. This way, AI-powered chatbots free up customer support agents, saving the organization millions of dollars worth of time, and resources every year.
In addition to chatbots, here are the other popular AI-powered tools that you can leverage in your customer service roadmap in 2023.
- AI agent assist
- AI self-service
- IVR automation
- Virtual receptionists
- Sentiment analytics
- Voice search and translators
- Robotic Process Automation (RPA)
By accurately defining the role of AI in customer service operations, organizations can get the right help at the right time to their customers. This would answer all the questions related to the agent handling time, customer wait time, call abandonment rates, and adoption of self-service assists for different types of queries.
Laying a Solid Data Infrastructure for AI ML Processes
Contact centers are emerging as one of the top generators and users of data and analytics. Depending on the value, volume and variety of the contact center data generated every day and month, you could be focusing your strategy on establishing a reliable data infrastructure to turbocharge your AI ML processes. The recent partnership announcement between AWS and Salesforce pinpoints the importance of owning your data infrastructure and machine learning foundations for better success with customer data platforms (CDPs).
API automation and ops management is another key consideration for contact center strategy. Call centers use a plethora of tools and solutions for managing different aspects of their business. For success, contact center software is integrated with other software platforms for better data analytics and decision-making. Commonly, these would include integration with a CRM, CDP, Marketing Analytics, Sales intelligence and forecasting, and email marketing automation. With AI, this enterprise technology stack gets more complex and intertwined, confusing agents. Advanced APIs can improve the overall quality of service and agility in the transformation of key business processes. However, it requires high-tech skills and human supervision to manage API workflows. Plus, there is always a risk of overlooking data security and compliance. All these, and much more, can overwhelm contact center agents. Therefore, AI-powered CoPilots for no-code automation should be part of your contact center modernization best practices.
It’s only possible when you have a strong data management framework to tackle challenges in data mining, governance, automation and AI ML workflows. For any brand to succeed with a customer service strategy with AI, it is important to lay the foundations of data management at the earliest.
Contact centers can further enhance their AI-powered processes by unifying all of the customer and agent data from different sources, and create a harmonized data ecosystem for a robust AI ML model.
Customer support teams can unlock the true potential of their AI ML tools by adopting a robust, step-by-step data architectural, migration, and modernization framework to deploy CX best practices at scale. This solid framework in data infrastructure puts your AI ML capabilities in the driver’s seat, specifically designed to improve the quality of service with highly advanced NLP workflows.
Offer Multilingual Support 24×7
Does your contact center respond to customer queries from different regions?
Do you expect your human agents to be physically present at the contact center, address regional inquiries using traditional localized translation software, and deliver as per your organizational objectives?
If not, are you planning to hire more agents to meet new business demands?
Wait… AI can assist you in this transformation with multilingual chat support capabilities.
A customer service strategy with Artificial Intelligence capabilities offering multilingual round-the-clock interaction is no longer a nice-to-have, but rather a “must-have.”
You can acquire and retain customers from different parts of the world without restricting your contact center’s inbound and outbound communication due to language barriers!
It is likely that your customers speak and understand different languages. Therefore, it is important to tap into a multilingual customer support strategy that can take your CX delivery to unmatched levels.
Recent research also unraveled the importance of offering multilingual AI chatbot support to customers without disrupting their experience. 75% of consumers prefer to buy from brands that provide customer care in their native language. While English remains the most preferred language for communication with contact center agents, consumers who are competent English speakers favor brands that interact with them in a language of their choice (other than English). Now, finding a human customer support agent with multilingual skills is a tough talent acquisition challenge. That’s where AI live agent assist is such an important element in your contact center modernization strategy.
The recent advancements in conversational AI and AI agent assist have made it possible to onboard new solutions for multilingual contact center communication. AI-based tools automate and speed up digital communication across email triage and call routing workflows with the existing web and app-based chat support. As the AI Live Agent Assist ingests more contact center data and learns new techniques, it can quickly scale process automation for multilingual support to reduce customer friction.
What is great about starting with multilingual AI chatbot support?
You can retain up to 75% of your customers, reduce customer acquisition costs by more than five times, and increase engagement and loyalty by 300%, without ever escalating to a human agent!
So, here are the five benefits of adopting multilingual AI chatbot support in your contact center:
- Improved customer experiences powered by AI-based automation and personalization
- Reduced cost of hiring of human agents
- Increased customer loyalty and retention
- Boost in productivity
- 100% contact center transformation
Mitigate Bot Failures at All Cost
The mad, insensible and unplanned rush toward AI adoption for contact center transformation can result in over-automation and under-performance. Bot failures are one of the biggest challenges that ripple even the best of well-planned contact center strategies. A majority of contact center owners fail to predict and overcome bot failures in their daily use cases. The result — total loss of business reputation and irreversible customer churn. According to a report, one-third of the population are worried about chatbots making mistakes, while 43% would prefer to talk to only human agents instead of a chatbot.
So, how do you tackle this issue with bots?
Train your ML algorithms used in bots internally before exposing them to live chats and calls with customers. A customer service strategy with Artificial Intelligence and machine learning will flourish when you centralize your information / knowledge base and create a single source of truth for the bots, agents, and customers. Your contact center plan should focus on two things:
- Proper AI training
- Proper bot deployment
Doing these two activities together can reduce basic inbound inquiries by up to 86%; increase digital conversions by 30%, and improve both customer as well as employee experience.
Upskill Customer Agents with AI ML Training
A majority of contact centers are focused on automate-first and automate-only practices while deploying AI ML solutions. This means, that these contact centers lag behind the real objective of transitioning their traditional contact center operations with a seamless human-machine collaboration. When 90% of tasks start getting automated and routed to AI-powered agents, it leaves a lot in the “ambiguity” space for human workers, who are suddenly expected to do the heavy squatting using AI tools such as generative AI, text analytics, and visualization. This leaves a gaping hole in the skills inventory for AI-based contact centers, suddenly finding themselves grappling with the idea of delivering stellar personalization using AI, but not enough human connection to match expectations.
The result — no visible improvement in the CSAT scores despite deploying AI best practices in the contact center.
It is normal to think that you could thrive in the business with an AI-only approach. However, when you solely focus on the customer and use AI to force conversations with them, your communication begins to deteriorate, and so does your quality of service. An agent, who is trained in AI, can start developing personality profiles using predictive signals gathered from millions and millions of historical touchpoints.
But, are you looking for a data scientist, an AI engineer, or a customer support professional? Or, a single human who embodies these superskills, all in one?
How to use this limitation as a game-changer in your customer service strategy using Artificial Intelligence?
Since 2020, there has been explosive growth in the number of AI ML courses that are specifically designed for professionals and business leaders from the customer service and support industry. These courses are using AI and machine learning techniques to develop new learning models for human professionals. Some examples are virtual contact center simulation, gamification, and role-playing in contact centers. With AI, organizations can accelerate the training and development of new and existing workforce. AI-based immersive learning concepts not only help in defining the roles of a contact center agent in a fast-changing organization but also harness the power of no-code automation, conversational AI, and IVR setups that engage with the best-of-world Cloud-based tools and platforms such as Salesforce, Oracle, AWS, Google, Zendesk, and Microsoft.
So, if you are going to turbocharge your contact center deployment with world-class technologies such as AI, automation and edge computing, you can’t take your eyes off skills training. Your entire strategy depends on how successfully you manage to hire, train, and retain a skilled workforce. After all, your employee experience drives customer experience efforts, and there is no better proof of ROI in your contact center that focuses on agility, scalability, and future-proof growth.
You can gain immensely from gathering employee and customer feedback about the use of AI in contact center activities. Whether you are driving an AI-based campaign or agentless inbound call center operation, you can create a perfectly in-sync value-driven contact center with the best SaaS vendors in the contact center software industry. From taking care of your personalization to automating your repetitive tasks to helping you scale in a secured environment, finding the right AI vendor for your contact center needs is the pivot on which your entire strategy should be based.
So, what kind of contact center software features are you currently focusing on?
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